It seems that in nature, self-organised systems have become highly effective and adaptive - think of bees or ants foraging for food, termites building large air-conditioned towers, or a 'murmuration' of starlings swirling through the sky in unison. SWARM engineering, the latest company launched by Frost Data Capital, is applying many of the latest advancements in agent-based software, combined with leading research on deep and reinforcement learning, to enable machines to collaborate together as a team.

Anthony Howcroft, CEO of SWARM, believes that organisations have a tendency to become overly focused on the 'plumbing' of technology, especially in a new market like IoT, or a fashionable sector such as AI, "...while we are using advanced algorithms and approaches within SWARM, the key is that we help organisations solve hard problems, by putting their machines to work for them,' he said.

Anthony Howcroft, CEO & co-founder SWARM Engineering

He explains that the concept is to put a low-footprint agent on each device or machine (or in the cloud if there is a 'digital twin'), and direct the agents towards a goal, and then let them self-organise and optimise the process by communicating and collaborating as a team. This does imply a level of machine learning, and Howcroft confirmed that "the agents learn at many levels - independently, and as a swarm too. We have the ability to deploy different learning algorithms based on the business scenario. So for example, in a blending example we are looking at Q-Learning, a type of reinforcement learning pioneered by Chris Watkins and famously used as the basis for the IBM Watson system that beet Lee Sedol in the Go challenge."

We look forward to seeing how SWARM develops, and the type of problems that they tackle. We asked Howcroft where the company was finding initial traction and he commented that "...there's a lot of interest by organisations that have large numbers of devices in a reasonably dense environment - like smart cities or mining. Then there are the industrial equipment manufacturers who are looking at how to add more value to their customers, and are fascinated by the concept of collaborating machines. One of the first areas where we've seen serious interest though, is in supply chain - especially in food production, and oil & gas - starting with the refinery blending issue. The opportunities for machines to solve problems by working together are huge, and our challenge is to focus on one or two specific scenarios in the short term. Once people see the benefits, and gain trust in the machines to deliver, we believe this will spread like wildfire through a value chain."